For motivation purpose, imagine the following continuous pattern matching problem. Given are two continuous pictures, each consisting of unicolor regions; one picture is called the scene and the other the pattern. The problem is to find all occurrences of the pattern in the scene. As a step towards efficient algorithmic handling of the continuous pattern matching problem by computers, where discretized representations are involved, we consider in this paper a two-dimensional pattern matching problem where the pattern and the text are specified in terms of exemplar digitized images. From the wider perspective of areas such as computer vision or image processing, our problem definitions identify an important gap in the fundamental theory of image formation and image processing - how to determine, even in the absence of noise, if a digitized image of a scene could contain an image of a given pattern?.
|Title of host publication||Combinatorial Pattern Matching - 4th Annual Symposium, CPM 1993, Proceedings|
|Editors||Alberto Apostolico, Alberto Apostolico, Maxime Crochemore , Zvi Galil, Zvi Galil, Udi Manber|
|Number of pages||18|
|State||Published - 1993|
|Event||Conference of the European Society for Fuzzy Logic and Technology, EUSFLAT 2017 and 16th International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets, IWIFSGN 2017 - Warsaw, Poland|
Duration: 11 Sep 2017 → 15 Sep 2017
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Conference||Conference of the European Society for Fuzzy Logic and Technology, EUSFLAT 2017 and 16th International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets, IWIFSGN 2017|
|Period||11/09/17 → 15/09/17|
Bibliographical noteFunding Information:
* Partially supported by the New York State Science and Technology Foundation Center for Advanced Technology. ** Partially supported by NSF grants CCR-8906949 and CCR-9111348.
© Springer-Verlag Berlin Heidelberg 1993.
ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science (all)